initial commit: ts time series analysis library v0.1.0

- 354 financial and mathematical time-series indicators
- Uniform C11 API with consistent function signatures
- 349 passing tests with -Werror
- Static and shared library builds
- pkg-config integration
- Python bindings
- Fuzzing and sanitizer support
- Security hardening flags

1 files changed, 94 insertions, 0 deletions

diff --git a/lib/gaussian_quantile.c b/lib/gaussian_quantile.c
new file mode 100644
index 0000000..337262c
--- /dev/null
+++ b/lib/gaussian_quantile.c
@@ -0,0 +1,94 @@
+// Gaussian Quantile
+//
+// gaussian_quantile
+//
+// Gaussian quantile function (inverse CDF)
+//
+// Q(p) = Φ^(-1)(p)
+//
+// Inputs:    1
+// Outputs:   1
+// Constants: 0
+
+
+#include <math.h>
+#include "ts.h"
+
+
+ts_parameter_t const ts_gaussian_quantile_p = { .n_inputs = 1, .n_outputs = 1, .n_constants = 0, .params_size = 0 };
+
+uint_t ts_gaussian_quantile_offset( ts_constant_t const *c )
+{
+	( void )c;
+	return ( 0 );
+}
+
+int ts_gaussian_quantile(
+	fp_t * const *y, uint_t y_n,
+	fp_t const * const *x, uint_t x_n,
+	uint_t n, ts_constant_t const *c
+)
+{
+	TS_PROLOGUE( ts_gaussian_quantile_p );
+	(void)c;
+    /* Peter Acklam's approximation for inverse normal CDF */
+    /* Coefficients for rational approximation */
+    fp_t const a[] = {
+        -3.969683028665376e+01, 2.209460984245205e+02,
+        -2.759285104469687e+02, 1.383577518672690e+02,
+        -3.066479806614716e+01, 2.506628277459239e+00
+    };
+    fp_t const b[] = {
+        -5.447609879822406e+01, 1.615858368580409e+02,
+        -1.556989798598866e+02, 6.680131188771972e+01,
+        -1.328068155288572e+01
+    };
+    fp_t const cc[] = {
+        -7.784894002430993e-03, 3.223964580411365e-01,
+        -2.400758277161838e+00, -2.549732539343734e+00,
+        4.374664141464968e+00, 2.938163982698783e+00
+    };
+    fp_t const d[] = {
+        7.784695709041462e-03, 3.224671290700398e-01,
+        2.445134137142996e+00, 3.754408661907416e+00
+    };
+
+    fp_t const p_low = 0.02425;
+    fp_t const p_high = 1.0 - p_low;
+
+    for (uint_t i = 0; i < n; ++i)
+    {
+        fp_t p = x[0][i];
+        if (p <= 0.0)
+        {
+            y[0][i] = -INFINITY;
+            continue;
+        }
+        if (p >= 1.0)
+        {
+            y[0][i] = INFINITY;
+            continue;
+        }
+
+        fp_t q, r;
+
+        if (p < p_low) {
+            q = sqrt(-2.0 * log(p));
+            y[0][i] = -(((((cc[0]*q + cc[1])*q + cc[2])*q + cc[3])*q + cc[4])*q + cc[5]) /
+                      ((((d[0]*q + d[1])*q + d[2])*q + d[3])*q + 1.0);
+        } else if (p <= p_high) {
+            q = p - 0.5;
+            r = q * q;
+            y[0][i] = (((((a[0]*r + a[1])*r + a[2])*r + a[3])*r + a[4])*r + a[5])*q /
+                      (((((b[0]*r + b[1])*r + b[2])*r + b[3])*r + b[4])*r + 1.0);
+        } else {
+            q = sqrt(-2.0 * log(1.0 - p));
+            y[0][i] = (((((cc[0]*q + cc[1])*q + cc[2])*q + cc[3])*q + cc[4])*q + cc[5]) /
+                      ((((d[0]*q + d[1])*q + d[2])*q + d[3])*q + 1.0);
+        }
+    }
+	return 0;
+}
+
+
+